Hand sign detection

Question

I am trying to identify static hand signs. Confused with the libraries and algorithms I can use for the project.

What need to it identify hand signs and convert in to text. I managed to get the hand contour. Can you please tell me what is the best method to classify hand signs. Is it haar classifier, adaboost classifier, convex hull, orientation histograms, SVM, shift algorithm, or any thing else. And also pls give me some examples as well.

I tried opencv and emugcv both for image processing. what is best c++ or c# for a real time system.

Any help is highly appreciated. Thanks

Answer 1

I have implemented a handtracking for web applications in my master deggree. Basically, you should follow those steps:

1 - Detect features of skin color in a Region of Interest. Basically, put a frame in the screen and ask for the user put the hand.

2 - You should have a implementation of a lucas kanade tracker method. Basically, this alghorithm will ensure that your features are not lost through the frames.

3 - Try get more features for each 3 frames interval.

Answer 2

You can find the best trained cascade to detect hand using OpenCV from the GitHub...

https://github.com/Aravindlivewire/Opencv/blob/master/haarcascade/aGest.xml

Good luck...

Answer 3

I have made the following with OpenCV. Algorithm:

1. Skin detection made in HSV
2. Thinning (if pixel has zero neighbor than set zero)
3. Thicking (if pixel has neighbor nonzero then set it nonzero)

See this Wikipedia page for the details of these.

Answer 4

The people use many approaches, so I cannot give a unique. You could make some research using Google Scholar and use the keywords "hand sign", "recognition" and "detection".

Maybe you find some code with the help of Google. An example, the HandVu: http://www.movesinstitute.org/~kolsch/HandVu/HandVu.html

The haar classifier (method of Viola-Jones) help to detect hand, not to recognize them.

Good luck in your research!